Triple
T19587151
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Genie Award for Best Sound |
E490132
|
entity |
| Predicate | notableRecipient |
P108
|
FINISHED |
| Object |
Claude La Haye
Claude La Haye is a Canadian sound engineer recognized for his award-winning work in film, including receiving the Genie Award for Best Sound.
|
E2096509
|
NE FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Claude La Haye | Statement: [Genie Award for Best Sound, notableRecipient, Claude La Haye]
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Claude La Haye Triple: [Genie Award for Best Sound, notableRecipient, Claude La Haye]
Generated description
Claude La Haye is a Canadian sound engineer recognized for his award-winning work in film, including receiving the Genie Award for Best Sound.
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d8e8dd9374819098e36349b3211663 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e640523d10819091320a61456f6437 |
completed | April 20, 2026, 3:03 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a37180aa29c819086591578ea09658e |
completed | June 20, 2026, 10:45 p.m. |
| NEDg | Description generation | batch_6a3718c84ee481908c220b2564249159 |
completed | June 20, 2026, 10:48 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a37194fcaf48190b32ef74944391ffc |
completed | June 20, 2026, 10:50 p.m. |
Created at: April 10, 2026, 1:42 p.m.